Modeling Customer Lifetime With Dynamic Customer Feedback Information

New Perspectives in Business and Econometrics

Alexander Kulumbeg

Marketing Institutes MCA & RDS

Daniel Winkler

Introduction

Story

  • Contractual setting - curated shopping
  • Nation-wide apparel subscription box service provider
  • Female customers only


  • Monthly surprise boxes with clothes selected by a stylist (person)
  • Option for customer to approve or change something in the box
  • Once received - rating of each item by categories and with optional written feedback

Story II

Idea

  • Propensity to churn changes over time
  • Traditionally data is
    • hard to obtain
    • static / collected once
  • Written feedback contains (un)conscious pieces of information
  • Feedback changes over time
    • Stylist did a better/worse job than before
    • Clothes’ color/fit/cut/size/material is good/bad
    • Items did/didn’t adhere to the customer preferences stated in the quiz
    • …


  • What is hiding in the dynamic feedback (e.g., emotionality, eloquence, engagement…)?
  • How do these components influence the risk of customer attrition?
  • Can we identify other (latent) time-varying signals that affect customer lifetime?

Data

  • Information on
    • Orders
    • Feedback
    • App usage
    • Customer journey
    • Style preferences
    • Stylist performance
    • Previews of Boxes
  • ca. 57,000 unique customers
  • ca. 260,000 transactions
  • ca. 1,050,000 feedback items
  • Distilled into a box-level dataframe
    • User demographics
    • User contract length
    • User lifetime spending
    • Box-level feedback variables
      • Word count
      • Sentiment
      • Eloquence
      • …

Model

Model Details

Results I

Plot1

Results II

Plot2

Results III

Plot3

Results IV

Plot4

Conclusion

Discussion

New Perspectives in Business and Econometrics - 24 January 2023